Czech FOI Data Analysis is a solution for analyzing, calculating, and visualizing FOI (Freedom of Information) data efficiently.
It's faster and more flexible than using spreadsheets but requires some IT knowledge.
The Python Scripts process and visualize CSV data from the TERRA folder, generating interactive HTML plots.
Each plot compares two age groups. To interact with the plots, click on a legend entry to show/hide curves.
Download the processed plots for analysis from the Plot Results Folder. Or simply adapt and run the Python scripts to meet your own analysis requirements!
Dates are counted as the number of days since January 1, 2020, for easier processing. "AGE_2023" represents age on January 1, 2023.
The data can optionally be normalized per 100,000 for comparison.
Access the original Czech FOI data from a Freedom of Information request. To learn how the Pivot CSV files in the TERRA folder were created, see the wiki
Abbreviations: The figures are per age group from the CSV files in the TERRA folder:
| Deaths | Definition | Population/Doses | Definition |
|---|---|---|---|
| NUM_D | Number deaths | NUM_POP | Total people |
| NUM_DUVX | Number unvaxed deaths | NUM_UVX | Number of unvaxed people |
| NUM_DVX | Number vaxed deaths | NUM_VX | Number of vaxed people |
| NUM_DVD1-DVD7 | Number deaths doses 1 - 7 | NUM_VD1-VD7 | Number of vax doses 1 - 7 |
| NUM_DVDA | Number deaths from all doses | NUM_VDA | Total number of all vax doses (sum) |
Interactive html plot of the Czech FOI data.
Age group comparison Pearson correlation 1st Derivate significance: AG_70-74 vs 75-79
%202D%206-Axis%20age-compare%20rolling-mean%20significance-1D-2D%20same-scale%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300/AH)%202D%206-Axis%20age-compare%20rolling-mean%20significance-1D-2D%20same-scale%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300%20AG_70-74%20vs%2075-79.png)
The first derivative represents speed because it measures how fast something changes over time. The second derivative represents acceleration as it measures how fast the speed (or first derivative) changes over time, showing how quickly the speed is increasing or decreasing.
Age group comparison Pearson correlation 2nd Derivate significance: AG_70-74 vs 75-79
%202D%206-Axis%20age-compare%20rolling-mean%20significance-1D-2D%20same-scale%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300/AH)%202D%206-Axis%20age-compare%20rolling-mean%20significance%202D%20same-scale%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300%20AG_70-74%20vs%2075-79.png)
The py script ending with same-scale uses the same y-axis scale for both age groups. Use this version to compare similar age groups. The file ending with different-scale uses different y-axes with different scales for each age group.
Decay Calcualtion and rolling correlation significance and shift: AG_50-54 vs 75-79
Decay Time - calculates the number of days per day retroactively after a certain percentage has died
%202D%206-Axis%20age-compare%20roll-mean%20sig-1D-2D%20cor-shift%20decay-hist-cor%20same-scale%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300%20AG_DIFF%2025Y/AI)%202D%206-Axis%20age-compare%20roll-mean%20sig-1D-2D%20cor-shift%20decay-hist-cor%20same-scale%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300%20AG_DIFF%2025Y%20AG_50-54%20vs%2075-79.png)
Simulation of deaths for rare dAEFIs, and attempts to back-calculate the frequency : AG_50-54 vs 75-79
In the simulation, the baseline without the dAEFIs is known , in reality it is unknown.
Here, I didn't use the czech FOI mortality data. Instead, I simulated the death curves using modulated sine waves.
%20backcalc%20sin%20dAEFI%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300%20AG_DIFF%2025Y/AI)%20backcalc%20sin%20dAEFI%201D2D-MEAN%20POP-D%20N-CUM-D%20N%20AVG_30%20CORR_300%20AG_DIFF%2025Y%20AG_50-54%20vs%2075-79.png)
If the baseline without the dAEFIs is known, the frequency of rare events (1 per 10,000) can be calculated.
However, I have struggled to find a reliable method to calculate the frequency of rare events,
when only the curve including the dAEFIs is available (real-world data) !
- Python 3.12.5 to run the scripts.
- Visual Studio Code 1.92.2 to edit and run scripts.
- Optional - DB Browser for SQLite 3.13.0 for database creation, SQL queries, and CSV export.
The results have not been checked for errors. Neither methodological nor technical checks or data cleansing have been performed.